Relevant bibliographies by topics / Detection codes

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Detection codes'

Author: Grafiati
Published: 28 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Detection codes"

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Alekseev, Maksim. "On Strengthening of Weak Algebraic Manipulation Detection Codes." International Journal of Embedded and Real-Time Communication Systems 6, no. 2 (2015): 1–26. http://dx.doi.org/10.4018/ijertcs.2015040101.

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Algebraic manipulation detection codes were introduced in 2008 to protect data against a special type of its modification – an algebraic manipulation. There are three classes of codes: weak, strong and stronger ones. Weak codes detect only weak algebraic manipulations, while strong and stronger are capable to detect both weak and strong manipulations. In this paper, a method to transform codes from weak to stronger is described resulting in a construction of generalized robust codes. The proposed construction forms the second known family of stronger AMD codes. Codes provide simple procedures
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Cramer, Ronald, Serge Fehr, and Carles Padró. "Algebraic manipulation detection codes." Science China Mathematics 56, no. 7 (2013): 1349–58. http://dx.doi.org/10.1007/s11425-013-4654-5.

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Ford, Elizabeth, John A. Carroll, Helen E. Smith, Donia Scott, and Jackie A. Cassell. "Extracting information from the text of electronic medical records to improve case detection: a systematic review." Journal of the American Medical Informatics Association 23, no. 5 (2016): 1007–15. http://dx.doi.org/10.1093/jamia/ocv180.

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Abstract Background Electronic medical records (EMRs) are revolutionizing health-related research. One key issue for study quality is the accurate identification of patients with the condition of interest. Information in EMRs can be entered as structured codes or unstructured free text. The majority of research studies have used only coded parts of EMRs for case-detection, which may bias findings, miss cases, and reduce study quality. This review examines whether incorporating information from text into case-detection algorithms can improve research quality. Methods A systematic search returne
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Das, P. K. "Codes on Key Errors." Cybernetics and Information Technologies 14, no. 2 (2014): 31–37. http://dx.doi.org/10.2478/cait-2014-0017.

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Abstract Coding theory has started with the intention of detection and correction of errors which have occurred during communication. Different types of errors are produced by different types of communication channels and accordingly codes are developed to deal with them. In 2013 Sharma and Gaur introduced a new kind of an error which will be termed “key error”. This paper obtains the lower and upper bounds on the number of parity-check digits required for linear codes capable for detecting such errors. Illustration of such a code is provided. Codes capable of simultaneous detection and correc
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Chen, Chaofan, Li Li, Li Wang, Shuai Wang, Xiangming Li, and George K. Karagiannidis. "Noncoherent Detection With Polar Codes." IEEE Access 7 (2019): 6362–72. http://dx.doi.org/10.1109/access.2018.2889498.

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Klove, T. "Optimal codes for error detection." IEEE Transactions on Information Theory 38, no. 2 (1992): 479–89. http://dx.doi.org/10.1109/18.119708.

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Condo, Carlo, Seyyed Ali Hashemi, and Warren J. Gross. "Blind Detection With Polar Codes." IEEE Communications Letters 21, no. 12 (2017): 2550–53. http://dx.doi.org/10.1109/lcomm.2017.2748940.

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Guo, Ying, and Guihua Zeng. "Quantum Event-Error Detection Codes." Journal of the Physical Society of Japan 74, no. 11 (2005): 2949–56. http://dx.doi.org/10.1143/jpsj.74.2949.

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Siddharth, A. "Error detection in numeric codes." Resonance 17, no. 7 (2012): 653–71. http://dx.doi.org/10.1007/s12045-012-0070-3.

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Shutao, Xia, and Fu Fangwei. "Combinatorial codes for error detection." Acta Mathematicae Applicatae Sinica 15, no. 4 (1999): 444–46. http://dx.doi.org/10.1007/bf02684046.

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Dissertations / Theses on the topic "Detection codes"

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Xu, Danfeng. "Iterative coded multiuser detection using LDPC codes." Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/27939.

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Multiuser detection (MUD) has been regarded as an effective technique for combating cochannel interference (CCI) in time-division multiple access (TDMA) systems and multiple access interference (MAI) in code-division multiple access (CDMA) systems. An optimal multiuser detector for coded multiuser systems is usually practically infeasible due to the associated complexity. An iterative receiver consisting of a soft-input soft-output (SISO) multiuser detector and a bank of SISO single user decoders can provide a system performance which approaches to that of single user system after a few itera
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Schiffel, Ute. "Hardware Error Detection Using AN-Codes." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-69872.

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Due to the continuously decreasing feature sizes and the increasing complexity of integrated circuits, commercial off-the-shelf (COTS) hardware is becoming less and less reliable. However, dedicated reliable hardware is expensive and usually slower than commodity hardware. Thus, economic pressure will most likely result in the usage of unreliable COTS hardware in safety-critical systems. The usage of unreliable, COTS hardware in safety-critical systems results in the need for software-implemented solutions for handling execution errors caused by this unreliable hardware. In this thesis, we pr
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Xiao, Jiaxi. "Information theoretic approach in detection and security codes." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43620.

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Signal detection plays a critical role in realizing reliable transmission through communication systems. In this dissertation, by applying information theoretic approach, efficient detection schemes and algorithms are designed for three particular communication systems. First, a computation efficient coding and detection algorithm is developed to decode two dimensional inter-symbol interference (ISI) channels. The detection algorithm significantly reduces the computation complexity and makes the proposed equalization algorithm applicable. A new metric, the post-detection mutual information (PM
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Gu, Yu. "Noncoherent communications using space-time trellis codes." Thesis, University of Canterbury. Electrical and Computer Engineering, 2008. http://hdl.handle.net/10092/1252.

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In the last decade much interest has been shown in space-time trellis codes (STTCs) since they can offer coding gain along with the ability to exploit the space and time diversity of MIMO channels. STTCs can be flexibly designed by trading off performance versus complexity. The work of Dayal [1] stated that if training symbols are used together with data symbols, then a space-time code can be viewed as a noncoherent code. The authors of [1] described the migration from coherent space-time codes to training assisted noncoherent space-time codes. This work focuses on the development of training
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Katz, Ettie. "Trellis codes for multipath fading ISI channels with sequential detection." Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/13908.

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Oruç, Özgür Altınkaya Mustafa Aziz. "Differential and coherent detection schemes for space-time block codes/." [s.l.]: [s.n.], 2002. http://library.iyte.edu.tr/tezler/master/elektrikveelektronikmuh/T000133.pdf.

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Knopp, Raymond. "Module-phase-codes with non-coherent detection and reduced-complexity decoding." Thesis, McGill University, 1993. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=68034.

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This thesis considers M-ary phase coding for the non-coherent AWGN channel. More precisely, we develop block-coded MPSK modulation schemes specifically for non-coherent block detection which significantly surpass the performance of ideal uncoded coherent MPSK. A class of block codes which are well-matched to MPSK modulation, called module-phase codes, is presented. The algebraic framework used for defining these codes relies on elements of module theory which are discussed along with a method for constructing such codes for non-coherent detection. It is shown that differential encoding, when c
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Valenti, Matthew C. "Iterative Detection and Decoding for Wireless Communications." Diss., Virginia Tech, 1999. http://hdl.handle.net/10919/28290.

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Turbo codes are a class of forward error correction (FEC) codes that offer energy efficiencies close to the limits predicted by information theory. The features of turbo codes include parallel code concatenation, recursive convolutional encoding, nonuniform interleaving, and an associated iterative decoding algorithm. Although the iterative decoding algorithm has been primarily used for the decoding of turbo codes, it represents a solution to a more general class of estimation problems that can be described as follows: a data set directly or indirectly drives the state transitions of two or
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Xu, Chang. "Inconsistency detection and resolution for context-aware pervasive computing /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?CSED%202008%20XU.

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Albayrak, Aras. "Automatic Pose and Position Estimation by Using Spiral Codes." Thesis, Högskolan i Halmstad, Halmstad Embedded and Intelligent Systems Research (EIS), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-27175.

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This master thesis is about providing the implementation of synthesis, detection of spiral symbols and estimating the pan/tilt angle and position by using camera calibration. The focus is however on the latter, the estimation of parameters of localization. Spiral symbols are used to be able to give an object an identity as well as to locate it. Due to the spiral symbol´s characteristic shape, we can use the generalized structure tensor (GST) algorithm which is particularly efficient to detect different members of the spiral family. Once we detect spirals, we know the position and identity para
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Books on the topic "Detection codes"

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Kløve, Torleiv. Codes for error detection. World Scientific, 2007.

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Gössel, Michael. Error detection circuits. McGraw-Hill, 1993.

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Crow, Judy. Model-based reconfiguration: Diagnosis and recovery. National Aeronautics and Space Administration, Langley Research Center, 1994.

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Leacock, Claudia. Automated grammatical error detection for language learners. Morgan & Claypool, 2010.

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Thompson, Michael W. Concatenated coding using trellis-coded modulation: Final report : NAG 9-767. National Aeronautics and Space Administration, 1997.

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Freeman, Jon C. Introduction to forward-error-correcting coding. NationalAeronautics and Space Administration, Office of Management, Scientific and Technical Information Branch, 1996.

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Freeman, Jon C. Introduction to forward-error-correcting coding. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1996.

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Freeman, Jon C. Introduction to forward-error-correcting coding. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1996.

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Freeman, Jon C. Introduction to forward-error-correcting coding. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1996.

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Kløve, Torleiv, and Valery I. Korzhik. Error Detecting Codes. Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-2309-3.

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Book chapters on the topic "Detection codes"

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Gonzalez, Diego L. "Error Detection and Correction Codes." In Biosemiotics. Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6340-4_17.

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Wu, Zining. "Turbo Codes and Turbo Equalization." In Coding and Iterative Detection for Magnetic Recording Channels. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4565-1_2.

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Wu, Zining. "Low-Density Parity-Check Codes." In Coding and Iterative Detection for Magnetic Recording Channels. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4565-1_3.

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Elkhadir, Zyad, Khalid Chougdali, and Mohammed Benattou. "A Median Nearest Neighbors LDA for Anomaly Network Detection." In Codes, Cryptology and Information Security. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55589-8_9.

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Jafargholi, Zahra, and Daniel Wichs. "Tamper Detection and Continuous Non-malleable Codes." In Theory of Cryptography. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46494-6_19.

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Wu, Zining. "Interleaved Parity Check Codes and Reduced Complexity Detection." In Coding and Iterative Detection for Magnetic Recording Channels. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4565-1_5.

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Lugiez, Denis. "Multivariate polynomial factoring and detection of true factors." In Applied Algebra, Algorithmics and Error-Correcting Codes. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/3-540-16767-6_62.

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Methods, Algebraic, and F. S. Vainstein. "Error detection and correction in numerical computations." In Applied Algebra, Algebraic Algorithms and Error-Correcting Codes. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/3-540-54522-0_133.

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Lin, Fuchun, Reihaneh Safavi-Naini, and Pengwei Wang. "Codes for Detection of Limited View Algebraic Tampering." In Information Security and Cryptology. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54705-3_19.

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Pintus, Maurizio. "Analysis of Neural Codes for Near-Duplicate Detection." In Advanced Concepts for Intelligent Vision Systems. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01449-0_30.

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Conference papers on the topic "Detection codes"

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Giard, Pascal, Alexios Balatsoukas-Stimming, and Andreas Burg. "Blind detection of polar codes." In 2017 IEEE International Workshop on Signal Processing Systems (SiPS). IEEE, 2017. http://dx.doi.org/10.1109/sips.2017.8109977.

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Picard, Justin, Paul Landry, and Michael Bolay. "Counterfeit detection with QR codes." In DocEng '21: ACM Symposium on Document Engineering 2021. ACM, 2021. http://dx.doi.org/10.1145/3469096.3474924.

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Qi, Gang, Xiaoli Yang, and Wei Fan. "LDPC codes in wireless optical communication application." In ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, edited by Keith E. Wilson, Jing Ma, Liren Liu, Huilin Jiang, and Xizheng Ke. SPIE, 2013. http://dx.doi.org/10.1117/12.2031610.

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Sobron, Iker, Maitane Barrenechea, Pello Ochandiano, Lorena Martinez, Mikel Mendicute, and Jon Altuna. "Low-complexity detection of golden codes in LDPC-coded OFDM systems." In ICASSP 2011 - 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2011. http://dx.doi.org/10.1109/icassp.2011.5946692.

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Arslan, Suayb S., Jaewook Lee, and Turguy Goker. "Embedding Noise Prediction Into List-Viterbi Decoding Using Error Detection Codes for Magnetic Tape Systems." In ASME 2013 Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/isps2013-2835.

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A List–Viterbi detector produces a rank ordered list of the N globally best candidates in a trellis search. A List–Viterbi detector structure is proposed that incorporates the noise prediction with periodic state-metric updates based on outer error detection codes (EDCs). More specifically, a periodic decision making process is utilized for a non-overlapping sliding windows of P bits based on the use of outer EDCs. In a number of magnetic recording applications, Error Correction Coding (ECC) is adversely effected by the presence of long and dominant error events. Unlike the conventional post p
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Naydenova, Irina, and Torleiv Klove. "Large proper codes for error detection." In 2006 IEEE Information Theory Workshop - ITW '06 Chengdu. IEEE, 2006. http://dx.doi.org/10.1109/itw2.2006.323781.

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Zhen Wang, Mark Karpovsky, and Berk Sunar. "Multilinear codes for robust error detection." In 2009 15th IEEE International On-Line Testing Symposium (IOLTS 2009). IEEE, 2009. http://dx.doi.org/10.1109/iolts.2009.5196002.

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Pingping Shang, Sooyoung Kim, and Kwonhue Choi. "Soft ZF MIMO detection for turbo codes." In 2010 IEEE 6th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). IEEE, 2010. http://dx.doi.org/10.1109/wimob.2010.5644980.

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Ren, Xiaofeng, and Deva Ramanan. "Histograms of Sparse Codes for Object Detection." In 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2013. http://dx.doi.org/10.1109/cvpr.2013.417.

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Moon, J. J., and L. R. Carley. "Sequeuce detection on run-length-limited codes." In Twenty-Third Asilomar Conference on Signals, Systems and Computers, 1989. IEEE, 1989. http://dx.doi.org/10.1109/acssc.1989.1200834.

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Reports on the topic "Detection codes"

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Wolf, Jack K. A Study of Error Detection and Correction Codes. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada162196.

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Heinstein, M. W., S. W. Attaway, J. W. Swegle, and F. J. Mello. A general-purpose contact detection algorithm for nonlinear structural analysis codes. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10175733.

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May, Elebeoba Eni, Mark Daniel Rintoul, Anna Marie Johnston, Richard J. Pryor, William Eugene Hart, and Jean-Paul Watson. Detection and reconstruction of error control codes for engineered and biological regulatory systems. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/918239.

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Viterbi, Andrew J., Jack K. Wolf, Lyle J. Fredrickson, Jeff A. Levin, and Robert D. Blakeney. Research in Mathematics and Computer Science: Calculation of the Probability of Undetected Error for Certain Error Detection Codes. Phase 2. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada238234.

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Crawford, R., P. Kerchen, K. Levitt, R. Olsson, M. Archer, and M. Casillas. Automated assistance for detecting malicious code. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10176903.

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Spielman, R. X-Ray Detector: An x-ray radiation detector design code. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/6908044.

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Shaver, Mark W., Andrew M. Casella, Richard S. Wittman, and John W. Hayes. Evaluation and Testing of the ADVANTG Code on SNM Detection. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1096695.

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Gentry, S. M. Detection optimization using linear systems analysis of a coded aperture laser sensor system. Office of Scientific and Technical Information (OSTI), 1994. http://dx.doi.org/10.2172/10187583.

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Neogi, Orgho. Search for Dark Matter in a Coannihilation Codex Model With CMS Detector. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1496031.

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Wen, Qingsong, Minzhen Ren, and Xiaoli Ma. Fixed-point Design of the Lattice-reduction-aided Iterative Detection and Decoding Receiver for Coded MIMO Systems. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada586964.

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